Overview

Dataset statistics

Number of variables15
Number of observations2776
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory325.4 KiB
Average record size in memory120.0 B

Variable types

Numeric15

Warnings

gross_revenue is highly correlated with qtde_itemsHigh correlation
qtde_items is highly correlated with gross_revenueHigh correlation
avg_ticket is highly skewed (γ1 = 51.91947145) Skewed
frequency_purchase is highly skewed (γ1 = 47.4307901) Skewed
df_index has unique values Unique
recency_days has 34 (1.2%) zeros Zeros
returns has 1483 (53.4%) zeros Zeros

Reproduction

Analysis started2021-05-25 14:56:26.609981
Analysis finished2021-05-25 14:56:54.997475
Duration28.39 seconds
Software versionpandas-profiling v2.13.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct2776
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2249.470101
Minimum0
Maximum5695
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:55.126165image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile181.5
Q1896.25
median2057
Q33409.25
95-th percentile4956.75
Maximum5695
Range5695
Interquartile range (IQR)2513

Descriptive statistics

Standard deviation1526.32928
Coefficient of variation (CV)0.6785283696
Kurtosis-0.9557705037
Mean2249.470101
Median Absolute Deviation (MAD)1237
Skewness0.3806980956
Sum6244529
Variance2329681.071
MonotonicityStrictly increasing
2021-05-25T11:56:55.255814image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01
 
< 0.1%
6231
 
< 0.1%
6111
 
< 0.1%
26601
 
< 0.1%
6131
 
< 0.1%
26621
 
< 0.1%
6151
 
< 0.1%
6171
 
< 0.1%
6191
 
< 0.1%
26701
 
< 0.1%
Other values (2766)2766
99.6%
ValueCountFrequency (%)
01
< 0.1%
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
ValueCountFrequency (%)
56951
< 0.1%
56851
< 0.1%
56791
< 0.1%
56541
< 0.1%
56481
< 0.1%

customer_id
Real number (ℝ≥0)

Distinct2768
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15278.38473
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:55.390074image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12614.5
Q113804.75
median15240.5
Q316779.25
95-th percentile17950.25
Maximum18287
Range5940
Interquartile range (IQR)2974.5

Descriptive statistics

Standard deviation1721.094452
Coefficient of variation (CV)0.1126489797
Kurtosis-1.211274453
Mean15278.38473
Median Absolute Deviation (MAD)1488.5
Skewness0.01533260642
Sum42412796
Variance2962166.111
MonotonicityNot monotonic
2021-05-25T11:56:55.521704image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
123702
 
0.1%
124572
 
0.1%
124312
 
0.1%
123942
 
0.1%
124222
 
0.1%
124172
 
0.1%
124552
 
0.1%
124292
 
0.1%
163841
 
< 0.1%
150021
 
< 0.1%
Other values (2758)2758
99.4%
ValueCountFrequency (%)
123471
< 0.1%
123481
< 0.1%
123521
< 0.1%
123561
< 0.1%
123581
< 0.1%
ValueCountFrequency (%)
182871
< 0.1%
182831
< 0.1%
182821
< 0.1%
182731
< 0.1%
182721
< 0.1%

gross_revenue
Real number (ℝ≥0)

HIGH CORRELATION

Distinct2763
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2904.817478
Minimum36.56
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:55.658211image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum36.56
5-th percentile264.575
Q1629.1775
median1170.87
Q32428.115
95-th percentile7473.3075
Maximum279138.02
Range279101.46
Interquartile range (IQR)1798.9375

Descriptive statistics

Standard deviation10923.05318
Coefficient of variation (CV)3.760323416
Kurtosis332.2194631
Mean2904.817478
Median Absolute Deviation (MAD)692.215
Skewness16.26775455
Sum8063773.32
Variance119313090.8
MonotonicityNot monotonic
2021-05-25T11:56:55.780634image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
379.652
 
0.1%
1080.482
 
0.1%
734.942
 
0.1%
6382.452
 
0.1%
2339.862
 
0.1%
3226.12
 
0.1%
745.062
 
0.1%
683.562
 
0.1%
3425.692
 
0.1%
3388.42
 
0.1%
Other values (2753)2756
99.3%
ValueCountFrequency (%)
36.561
< 0.1%
521
< 0.1%
52.21
< 0.1%
62.431
< 0.1%
68.841
< 0.1%
ValueCountFrequency (%)
279138.021
< 0.1%
259657.31
< 0.1%
194550.791
< 0.1%
168472.51
< 0.1%
140450.721
< 0.1%

recency_days
Real number (ℝ≥0)

ZEROS

Distinct252
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.55331412
Minimum0
Maximum372
Zeros34
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:55.915457image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q110
median29
Q373
95-th percentile211
Maximum372
Range372
Interquartile range (IQR)63

Descriptive statistics

Standard deviation68.34020913
Coefficient of variation (CV)1.208420942
Kurtosis3.457722286
Mean56.55331412
Median Absolute Deviation (MAD)23
Skewness1.902985869
Sum156992
Variance4670.384184
MonotonicityNot monotonic
2021-05-25T11:56:56.045888image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199
 
3.6%
486
 
3.1%
386
 
3.1%
285
 
3.1%
876
 
2.7%
1067
 
2.4%
967
 
2.4%
765
 
2.3%
1762
 
2.2%
2255
 
2.0%
Other values (242)2028
73.1%
ValueCountFrequency (%)
034
 
1.2%
199
3.6%
285
3.1%
386
3.1%
486
3.1%
ValueCountFrequency (%)
3721
 
< 0.1%
3661
 
< 0.1%
3601
 
< 0.1%
3583
0.1%
3541
 
< 0.1%

qtde_invoices
Real number (ℝ≥0)

Distinct55
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.058357349
Minimum2
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:56.181762image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median4
Q36
95-th percentile17
Maximum206
Range204
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.069472528
Coefficient of variation (CV)1.497018417
Kurtosis183.9608724
Mean6.058357349
Median Absolute Deviation (MAD)2
Skewness10.62312311
Sum16818
Variance82.25533193
MonotonicityNot monotonic
2021-05-25T11:56:56.324225image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2779
28.1%
3498
17.9%
4394
14.2%
5238
 
8.6%
6174
 
6.3%
7138
 
5.0%
897
 
3.5%
970
 
2.5%
1055
 
2.0%
1154
 
1.9%
Other values (45)279
 
10.1%
ValueCountFrequency (%)
2779
28.1%
3498
17.9%
4394
14.2%
5238
 
8.6%
6174
 
6.3%
ValueCountFrequency (%)
2061
< 0.1%
1991
< 0.1%
1241
< 0.1%
971
< 0.1%
912
0.1%

qtde_items
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1635
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1700.85987
Minimum2
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:56.468649image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile119.75
Q1330.75
median708
Q31488
95-th percentile4642.5
Maximum196844
Range196842
Interquartile range (IQR)1157.25

Descriptive statistics

Standard deviation6076.80334
Coefficient of variation (CV)3.572783065
Kurtosis438.0048531
Mean1700.85987
Median Absolute Deviation (MAD)455
Skewness17.32743146
Sum4721587
Variance36927538.84
MonotonicityNot monotonic
2021-05-25T11:56:56.606257image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31011
 
0.4%
2468
 
0.3%
1508
 
0.3%
2727
 
0.3%
12007
 
0.3%
2607
 
0.3%
2197
 
0.3%
3947
 
0.3%
2007
 
0.3%
3007
 
0.3%
Other values (1625)2700
97.3%
ValueCountFrequency (%)
21
< 0.1%
161
< 0.1%
171
< 0.1%
191
< 0.1%
201
< 0.1%
ValueCountFrequency (%)
1968441
< 0.1%
809971
< 0.1%
802631
< 0.1%
773731
< 0.1%
699931
< 0.1%

qtde_products
Real number (ℝ≥0)

Distinct466
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.7100144
Minimum2
Maximum7838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:56.743076image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10
Q134
median72
Q3143
95-th percentile399.75
Maximum7838
Range7836
Interquartile range (IQR)109

Descriptive statistics

Standard deviation277.6619927
Coefficient of variation (CV)2.140636511
Kurtosis337.1889651
Mean129.7100144
Median Absolute Deviation (MAD)45
Skewness15.35820919
Sum360075
Variance77096.18218
MonotonicityNot monotonic
2021-05-25T11:56:56.875258image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2838
 
1.4%
3534
 
1.2%
2630
 
1.1%
2930
 
1.1%
2730
 
1.1%
2528
 
1.0%
3127
 
1.0%
1527
 
1.0%
1927
 
1.0%
3326
 
0.9%
Other values (456)2479
89.3%
ValueCountFrequency (%)
211
0.4%
313
0.5%
416
0.6%
516
0.6%
624
0.9%
ValueCountFrequency (%)
78381
< 0.1%
56731
< 0.1%
50951
< 0.1%
45801
< 0.1%
26981
< 0.1%

qtde_unique_products
Real number (ℝ≥0)

Distinct340
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.32600865
Minimum1
Maximum1786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:57.011474image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q129
median57
Q3105
95-th percentile239.25
Maximum1786
Range1785
Interquartile range (IQR)76

Descriptive statistics

Standard deviation98.6969663
Coefficient of variation (CV)1.184467706
Kurtosis80.66590932
Mean83.32600865
Median Absolute Deviation (MAD)33
Skewness6.352503105
Sum231313
Variance9741.091158
MonotonicityNot monotonic
2021-05-25T11:56:57.140994image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3738
 
1.4%
2437
 
1.3%
2636
 
1.3%
2535
 
1.3%
3334
 
1.2%
2834
 
1.2%
3032
 
1.2%
1832
 
1.2%
1530
 
1.1%
5229
 
1.0%
Other values (330)2439
87.9%
ValueCountFrequency (%)
119
0.7%
213
0.5%
318
0.6%
418
0.6%
523
0.8%
ValueCountFrequency (%)
17861
< 0.1%
17661
< 0.1%
13221
< 0.1%
11181
< 0.1%
8841
< 0.1%

avg_ticket
Real number (ℝ≥0)

SKEWED

Distinct2768
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.32262173
Minimum2.150588235
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:57.269328image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum2.150588235
5-th percentile4.853198841
Q112.43801146
median17.94212763
Q325.10360946
95-th percentile88.38245902
Maximum56157.5
Range56155.34941
Interquartile range (IQR)12.665598

Descriptive statistics

Standard deviation1070.663297
Coefficient of variation (CV)20.46272266
Kurtosis2720.281153
Mean52.32262173
Median Absolute Deviation (MAD)6.347201302
Skewness51.91947145
Sum145247.5979
Variance1146319.896
MonotonicityNot monotonic
2021-05-25T11:56:57.391653image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.527764712
 
0.1%
27.392489272
 
0.1%
17.988421052
 
0.1%
34.631016952
 
0.1%
43.21922
 
0.1%
17.628961752
 
0.1%
36.046808512
 
0.1%
20.636686752
 
0.1%
5.2065863451
 
< 0.1%
11.747878791
 
< 0.1%
Other values (2758)2758
99.4%
ValueCountFrequency (%)
2.1505882351
< 0.1%
2.43251
< 0.1%
2.4623711341
< 0.1%
2.5112413791
< 0.1%
2.5153333331
< 0.1%
ValueCountFrequency (%)
56157.51
< 0.1%
4453.431
< 0.1%
1687.21
< 0.1%
952.98751
< 0.1%
872.131
< 0.1%

avg_recency_days
Real number (ℝ≥0)

Distinct305
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.47478386
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:57.535502image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13
Q134
median59
Q399
95-th percentile224
Maximum366
Range365
Interquartile range (IQR)65

Descriptive statistics

Standard deviation66.56127228
Coefficient of variation (CV)0.8481867551
Kurtosis3.685559012
Mean78.47478386
Median Absolute Deviation (MAD)30
Skewness1.830817529
Sum217846
Variance4430.402968
MonotonicityNot monotonic
2021-05-25T11:56:57.679006image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3540
 
1.4%
7039
 
1.4%
5537
 
1.3%
3136
 
1.3%
4536
 
1.3%
2136
 
1.3%
2535
 
1.3%
2634
 
1.2%
4634
 
1.2%
3833
 
1.2%
Other values (295)2416
87.0%
ValueCountFrequency (%)
19
0.3%
25
0.2%
38
0.3%
48
0.3%
55
0.2%
ValueCountFrequency (%)
3661
< 0.1%
3651
< 0.1%
3641
< 0.1%
3631
< 0.1%
3572
0.1%

returns
Real number (ℝ≥0)

ZEROS

Distinct23
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.124639769
Minimum0
Maximum45
Zeros1483
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:57.811099image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum45
Range45
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.375314082
Coefficient of variation (CV)2.112066589
Kurtosis106.8785178
Mean1.124639769
Median Absolute Deviation (MAD)0
Skewness7.760908921
Sum3122
Variance5.642116987
MonotonicityNot monotonic
2021-05-25T11:56:57.930236image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
01483
53.4%
1657
23.7%
2270
 
9.7%
3139
 
5.0%
492
 
3.3%
538
 
1.4%
632
 
1.2%
721
 
0.8%
98
 
0.3%
125
 
0.2%
Other values (13)31
 
1.1%
ValueCountFrequency (%)
01483
53.4%
1657
23.7%
2270
 
9.7%
3139
 
5.0%
492
 
3.3%
ValueCountFrequency (%)
451
< 0.1%
441
< 0.1%
351
< 0.1%
271
< 0.1%
211
< 0.1%

latitude
Real number (ℝ)

Distinct28
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.48420656
Minimum-25.274398
Maximum64.963051
Zeros0
Zeros (%)0.0%
Negative8
Negative (%)0.3%
Memory size21.8 KiB
2021-05-25T11:56:58.053290image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum-25.274398
5-th percentile50.503887
Q155.378051
median55.378051
Q355.378051
95-th percentile55.378051
Maximum64.963051
Range90.237449
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.1810818
Coefficient of variation (CV)0.09509327798
Kurtosis165.0199907
Mean54.48420656
Median Absolute Deviation (MAD)0
Skewness-11.5015348
Sum151248.1574
Variance26.84360861
MonotonicityNot monotonic
2021-05-25T11:56:58.172142image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
55.3780512516
90.6%
51.16569167
 
2.4%
46.22763858
 
2.1%
40.46366720
 
0.7%
50.50388719
 
0.7%
46.81818812
 
0.4%
39.39987211
 
0.4%
-25.2743988
 
0.3%
56.263927
 
0.3%
61.924117
 
0.3%
Other values (18)51
 
1.8%
ValueCountFrequency (%)
-25.2743988
0.3%
1.3520831
 
< 0.1%
31.0460511
 
< 0.1%
35.1264134
0.1%
35.9374961
 
< 0.1%
ValueCountFrequency (%)
64.9630511
 
< 0.1%
61.924117
0.3%
60.4720246
0.2%
60.1281614
0.1%
56.263927
0.3%

longitude
Real number (ℝ)

Distinct28
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.912515498
Minimum-106.346771
Maximum138.252924
Zeros0
Zeros (%)0.0%
Negative2553
Negative (%)92.0%
Memory size21.8 KiB
2021-05-25T11:56:58.291415image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum-106.346771
5-th percentile-3.435973
Q1-3.435973
median-3.435973
Q3-3.435973
95-th percentile8.227512
Maximum138.252924
Range244.599695
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.70248616
Coefficient of variation (CV)-5.596025845
Kurtosis134.0830004
Mean-1.912515498
Median Absolute Deviation (MAD)0
Skewness9.898730903
Sum-5309.143022
Variance114.5432099
MonotonicityNot monotonic
2021-05-25T11:56:58.417497image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
-3.4359732516
90.6%
10.45152667
 
2.4%
2.21374958
 
2.1%
-3.7492220
 
0.7%
4.46993619
 
0.7%
8.22751212
 
0.4%
-8.22445411
 
0.4%
133.7751368
 
0.3%
9.5017857
 
0.3%
25.7481517
 
0.3%
Other values (18)51
 
1.8%
ValueCountFrequency (%)
-106.3467711
 
< 0.1%
-95.7128911
 
< 0.1%
-19.0208351
 
< 0.1%
-8.243893
 
0.1%
-8.22445411
0.4%
ValueCountFrequency (%)
138.2529245
0.2%
133.7751368
0.3%
103.8198361
 
< 0.1%
34.8516121
 
< 0.1%
33.4298594
0.1%

frequency_purchase
Real number (ℝ≥0)

SKEWED

Distinct1228
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06179287837
Minimum0.005464480874
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:58.559468image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0.005464480874
5-th percentile0.008771929825
Q10.01587301587
median0.02451648234
Q30.04215136408
95-th percentile0.1178705525
Maximum34
Range33.99453552
Interquartile range (IQR)0.0262783482

Descriptive statistics

Standard deviation0.6691989062
Coefficient of variation (CV)10.82970925
Kurtosis2388.815848
Mean0.06179287837
Median Absolute Deviation (MAD)0.01079903541
Skewness47.4307901
Sum171.5370303
Variance0.447827176
MonotonicityNot monotonic
2021-05-25T11:56:58.709177image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0714285714316
 
0.6%
0.0476190476215
 
0.5%
0.030303030314
 
0.5%
0.0285714285714
 
0.5%
0.0158730158714
 
0.5%
0.142857142913
 
0.5%
0.0238095238113
 
0.5%
0.0645161290313
 
0.5%
0.117647058812
 
0.4%
0.02512
 
0.4%
Other values (1218)2640
95.1%
ValueCountFrequency (%)
0.0054644808741
< 0.1%
0.0054794520551
< 0.1%
0.0054945054951
< 0.1%
0.0055096418731
< 0.1%
0.0056022408962
0.1%
ValueCountFrequency (%)
341
 
< 0.1%
61
 
< 0.1%
41
 
< 0.1%
26
0.2%
1.51
 
< 0.1%

avg_basket_size
Real number (ℝ≥0)

Distinct974
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.47744574
Minimum1
Maximum297.8823529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2021-05-25T11:56:59.956179image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q110
median17
Q327.33333333
95-th percentile54.2125
Maximum297.8823529
Range296.8823529
Interquartile range (IQR)17.33333333

Descriptive statistics

Standard deviation17.84737266
Coefficient of variation (CV)0.8309820856
Kurtosis27.51624809
Mean21.47744574
Median Absolute Deviation (MAD)8
Skewness3.257325104
Sum59621.38938
Variance318.5287107
MonotonicityNot monotonic
2021-05-25T11:57:00.100831image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1345
 
1.6%
1730
 
1.1%
1130
 
1.1%
1428
 
1.0%
126
 
0.9%
7.525
 
0.9%
1525
 
0.9%
925
 
0.9%
2324
 
0.9%
9.524
 
0.9%
Other values (964)2494
89.8%
ValueCountFrequency (%)
126
0.9%
1.21
 
< 0.1%
1.251
 
< 0.1%
1.3333333332
 
0.1%
1.59
 
0.3%
ValueCountFrequency (%)
297.88235291
< 0.1%
1911
< 0.1%
135.33333331
< 0.1%
129.751
< 0.1%
125.751
< 0.1%

Interactions

2021-05-25T11:56:29.861812image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:29.977755image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:30.087976image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:30.207479image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:30.324960image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:30.443614image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:30.564184image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:30.682582image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:30.791968image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:30.907830image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:31.010543image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:31.126595image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:31.243415image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:31.355532image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:31.462787image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:31.569462image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:31.675523image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:31.780637image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:31.892656image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:32.009113image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:32.120312image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:32.227863image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:32.332496image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:32.449349image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:32.557181image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:32.665998image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:32.778166image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:32.895175image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:33.010413image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:33.124270image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:33.238767image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:33.353496image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:33.471736image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:33.593221image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:33.716760image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:33.840468image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:33.951530image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:34.067967image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:34.174959image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:34.281136image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:34.389792image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:34.505412image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:34.617697image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:34.732046image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:34.840549image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:34.948772image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:35.060484image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:35.178548image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:35.294467image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:35.407340image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:35.511844image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:35.621126image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:35.723006image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:35.831174image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:35.962780image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:36.095917image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:36.241710image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:36.383419image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:36.523609image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:36.661109image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:36.781150image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:36.898956image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:37.018309image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:37.139926image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:37.251870image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:37.363557image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:37.479738image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:37.595193image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:37.713595image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:37.837597image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:37.961475image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:38.082298image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:38.205900image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:38.329152image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:38.459379image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:38.588699image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:38.720119image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:38.860056image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:38.983525image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:39.115727image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:39.267594image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:39.387113image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:39.509308image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:39.636806image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:39.758236image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:39.867788image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:39.979405image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:40.100456image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:40.217554image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:40.332097image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:40.451091image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:40.571343image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:40.690112image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:40.806319image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:40.912359image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:41.018650image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:41.129076image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:41.243068image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:41.351999image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:41.458863image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:41.564719image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:41.672490image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:41.783713image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:41.895770image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:42.008639image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:42.121817image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:42.228305image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:42.339057image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:42.448685image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:42.562280image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:42.680866image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:42.805509image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:42.925593image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:43.036735image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:43.149656image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:43.261450image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:43.375180image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:43.494686image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:43.614037image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:43.734574image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:43.851461image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:43.966710image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:44.074178image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:44.182412image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:44.292601image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:44.408657image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:44.520926image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:44.640709image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:44.750348image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:44.856361image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:44.966561image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:45.078844image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:45.193142image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:45.309479image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:45.427953image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:45.539737image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:45.644443image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:45.767755image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:45.872645image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:45.982307image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.101023image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.200501image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.298457image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.397525image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.495881image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.598818image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.699796image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.800466image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.901744image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:46.995098image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:47.093842image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:47.184872image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:47.278253image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:47.381104image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:47.490179image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:47.597076image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:47.704876image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:47.814304image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:47.924555image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:48.038863image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:48.154065image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:48.269047image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:48.382300image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:48.500957image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:48.616486image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:48.722128image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:48.829060image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:48.944993image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:49.065485image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:49.180869image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:49.292122image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:49.408764image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:49.560577image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:49.713998image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:49.847608image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:49.984779image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:50.123440image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:50.251443image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:50.387124image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:50.513951image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:50.637546image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:50.779933image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:50.908116image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:51.055185image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:51.222217image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:51.385606image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:51.518912image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:51.633449image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:51.750144image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:51.871765image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:51.991547image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:52.129077image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:52.251224image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:52.363539image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:52.490560image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:52.613668image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:52.739518image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:52.854884image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:52.974814image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:53.093050image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:53.211865image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:53.336998image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:53.461066image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:53.584237image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:53.704058image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:53.819352image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:53.946695image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:54.076846image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:54.200301image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-25T11:56:54.321407image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Correlations

2021-05-25T11:57:00.235128image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-05-25T11:57:00.432848image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-05-25T11:57:00.631769image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-05-25T11:57:00.840423image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-05-25T11:56:54.587529image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
A simple visualization of nullity by column.
2021-05-25T11:56:54.886175image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

df_indexcustomer_idgross_revenuerecency_daysqtde_invoicesqtde_itemsqtde_productsqtde_unique_productsavg_ticketavg_recency_daysreturnslatitudelongitudefrequency_purchaseavg_basket_size
00178505391.21372.034.01733.0297.021.018.1522221.01.055.378051-3.43597334.0000008.735294
11130473232.5956.09.01390.0171.0105.018.90403552.07.055.378051-3.4359730.02839119.000000
22125836705.382.015.05028.0232.0114.028.90250026.02.046.2276382.2137490.04043115.466667
3313748948.2595.05.0439.028.024.033.86607192.00.055.378051-3.4359730.0179865.600000
4415100876.00333.03.080.03.01.0292.00000020.03.055.378051-3.4359730.0750001.000000
55152914623.3025.014.02102.0102.061.045.32647126.05.055.378051-3.4359730.0402307.285714
66146885630.877.021.03621.0327.0148.017.21978619.06.055.378051-3.4359730.05737715.285714
77178095411.9116.012.02057.061.046.088.71983639.02.055.378051-3.4359730.0336135.083333
881531160767.900.091.038194.02379.0567.025.5434644.027.055.378051-3.4359730.24396825.901099
99160982005.6387.07.0613.067.034.029.93477647.00.055.378051-3.4359730.0244769.428571

Last rows

df_indexcustomer_idgross_revenuerecency_daysqtde_invoicesqtde_itemsqtde_productsqtde_unique_productsavg_ticketavg_recency_daysreturnslatitudelongitudefrequency_purchaseavg_basket_size
2766561017290525.243.02.0404.0102.092.05.14941213.00.055.378051-3.4359730.15384647.000000
276756191478577.4010.02.084.03.02.025.8000005.00.055.378051-3.4359730.4000001.500000
2768562017254272.444.02.0252.0112.0100.02.43250011.00.055.378051-3.4359730.18181855.500000
2769563617232421.522.02.0203.036.030.011.70888912.00.055.378051-3.4359730.16666717.500000
2770563717468137.0010.02.0116.05.05.027.4000004.00.055.378051-3.4359730.5000002.500000
2771564813596697.045.02.0406.0166.0133.04.1990367.00.055.378051-3.4359730.28571469.000000
27725654148931237.859.02.0799.073.072.016.9568492.00.055.378051-3.4359731.00000036.500000
2773567914126706.137.03.0508.015.014.047.0753333.01.055.378051-3.4359731.0000005.000000
27745685135211092.391.03.0733.0435.0312.02.5112414.00.055.378051-3.4359730.333333135.333333
2775569515060301.848.04.0262.0120.080.02.5153331.00.055.378051-3.4359734.00000027.500000